算法1002

Gökçehan Kara, C. Özturan
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引用次数: 3

摘要

最大流量问题是最常见的网络流问题之一。这个问题涉及在具有流量能力的弧线的网络中找到两个指定节点之间的最大可能流量。推-重标签算法是解决这一问题最快的算法之一。提出了一种共享内存并行推标签算法。使用图形着色来避免线程之间的冲突,以进行并发的推送和重新标记操作。此外,使用原子指令更新目标节点的多余值,以防止竞争条件。实验表明,该算法对直径较小的宽图具有较强的竞争力。包括三个不同数据集的结果:计算机视觉问题、DIMACS挑战问题和KaHIP分区问题。将它们与现有的推标签和伪流实现进行比较。我们证明了在稀疏网络上使用基于着色的并行化技术可以实现高加速率。然而,我们也观察到伪流算法在密集和长网络上比推标签算法运行得更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm 1002
The maximum flow problem is one of the most common network flow problems. This problem involves finding the maximum possible amount of flow between two designated nodes on a network with arcs having flow capacities. The push-relabel algorithm is one of the fastest algorithms to solve this problem. We present a shared memory parallel push-relabel algorithm. Graph coloring is used to avoid collisions between threads for concurrent push and relabel operations. In addition, excess values of target nodes are updated using atomic instructions to prevent race conditions. The experiments show that our algorithm is competitive for wide graphs with low diameters. Results from three different data sets are included, computer vision problems, DIMACS challenge problems, and KaHIP partitioning problems. These are compared with existing push-relabel and pseudoflow implementations. We show that high speedup rates are possible using our coloring based parallelization technique on sparse networks. However, we also observe that the pseudoflow algorithm runs faster than the push-relabel algorithm on dense and long networks.
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